摘要
在管道运行时,由于管道摩阻、周围介质扩散等影响,使得测得的压力与流量信号带有很大的噪声,当噪声频率很宽时,自适应滤波器的参数设置比较困难,致使去噪效果不明显。为此,提出了一种基于小波分解的自适应滤波算法,该算法基于信号和噪声经小波变换后在不同尺度上有不同的特征,即先对信号进行小波多尺度分解,然后对各尺度分解的信号分别选用不同的滤波参数,进行自适应滤波处理。并用该方法对在管道泄漏实验中采集的信号进行降噪处理。结果表明,该方法比普通的自适应滤波方法更能有效地消除信号中的噪声。
When pipeline is running there are great noises in the measured pressure and flow signal due to the diffusion of medium around pipeline and rub resistance, and it is difficult to set the parameters of the adaptive filter for the wide frequency of noise, certainly, thus resulting bad de - noising effect. Adaptive filter based on wavelet analysis, which is based on different characteristics of signal with noise in different wavelet scales, is introduced. At first wavelet analysis is used to divide signal and processed them separately by adaptive filter. The method is used to eliminate the noise in the flow signal measured in pipeline leak detection experiment. The result indicates that the method can eliminate the noise in the signal more effectively than the usual filter.
出处
《计算机仿真》
CSCD
2006年第1期105-107,共3页
Computer Simulation
基金
辽宁省自然科学基金 20022159
关键词
小波分解
自适应滤波
管道
去噪
Wavelet analysis
Adaptive filter
Pipeline
De - noising
